The short-term effects of individual and mixed ambient air pollutants on suicide mortality: A case-crossover study.

It is critical to explore intervenable environmental factors in suicide mortality. Based on 30,688 suicide cases obtained from the Mortality Surveillance System of the Jiangsu Provincial Centre for Disease Control and Prevention, we utilized a case-crossover design, and found that the OR of suicide deaths increased by a maximum of 0.71 % (95 % CI: 0.09 %, 1.32 %), 0.68 % (95 % CI: 0.12 %, 1.25 %), 0.77 % (95 % CI: 0.19 %, 1.37 %), 2.95 % (95 % CI: 1.62 %, 4.29 %), 4.18 % (95 % CI: 1.55 %, 6.88 %), and 0.93 % (95 % CI: 0.10 %, 1.77 %), respectively, for per 10 µg/m3 increase in the particulate matter (PM) with diameters ≤ 2.5 µm (PM2.5), PM with diameters ≤ 10 µm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and per 0.1 mg/m3 increase in carbon monoxide (CO) concentrations with the conditional logistic regression analysis. People living in county-level cities were more susceptible. Particularly, a significant positive association was found between air pollutant mixture exposure and suicide deaths (OR=1.04,95 % CI: 1.01, 1.06). The excess fraction of suicide deaths due to air pollution reached a maximum of 8.07 %. In conclusion, we found associations between individual and mixed ambient air pollutants and suicide deaths, informing the development of integrated air pollution management and targeted measures for suicide prevention and intervention. ENVIRONMENTAL IMPLICATION: As a major contributor to the global burden of disease, air pollution was confirmed by accumulating studies to have adverse impact on mental health, and potentially lead to suicide deaths. However, systematic studies on the association between air pollution and suicide mortality are lacking. We explored the associations of multiple air pollutants and pollution mixtures with suicide deaths and assessed excess suicide mortality due to air pollution, emphasizing the importance of air pollution control on suicide prevention. Our study provides evidence to support mechanistic studies on the association between air pollution and suicide, and informs comprehensive air pollution management.

Metabolomic landscape of overall and common cancers in the UK Biobank: A prospective cohort study.

Information about the NMR metabolomics landscape of overall, and common cancers is still limited. Based on a cohort of 83,290 participants from the UK Biobank, we used multivariate Cox regression to assess the associations between each of the 168 metabolites with the risks of overall cancer and 20 specific types of cancer. Then, we applied LASSO to identify important metabolites for overall cancer risk and obtained their associations using multivariate cox regression. We further conducted mediation analysis to evaluate the mediated role of metabolites in the effects of traditional factors on overall cancer risk. Finally, we included the 13 identified metabolites as predictors in prediction models, and compared the accuracies of our traditional models. We found that there were commonalities among the metabolic profiles of overall and specific types of cancer: the top 20 frequently identified metabolites for 20 specific types of cancer were all associated with overall cancer; most of the specific types of cancer had common identified metabolites. Meanwhile, the associations between the same metabolite with different types of cancer can vary based on the site of origin. We identified 13 metabolic biomarkers associated with overall cancer, and found that they mediated the effects of traditional factors. The accuracies of prediction models improved when we added 13 identified metabolites in models. This study is helpful to understand the metabolic mechanisms of overall and a wide range of cancers, and our results also indicate that NMR metabolites are potential biomarkers in cancer diagnosis and prevention.

The impact of short-term exposures to ambient NO2, O3, and their combined oxidative potential on daily mortality.

It is widely recognized that air pollution exerts substantial detrimental effects in human health and the economy. The potential for harm is closely linked to the concentrations of pollutants like nitrogen dioxide (NO2) and ozone (O3), as well as their collective oxidative potential (OX). Yet, due to the challenges of directly monitoring OX as an independent factor and the influences of different substances' varying ability to contain or convey OX, uncertainties persist regarding its actual impact. To provide further evidence to the association between short-term exposures to NO2, O3, and OX and mortality, this study conducted multi-county time-series analyses with over-dispersed generalized additive models and random-effects meta-analyses to estimate the mortality data from 2014 to 2020 in Jiangsu, China. The findings reveal that short-term exposures to these pollutants are linked to increased risks of all-cause, cardiovascular, and respiratory mortality, where NO2 demonstrates 2.11% (95% confidence interval: 1.79%, 2.42%), 2.28% (1.91%, 2.66%), and 2.91% (2.13%, 3.69%) respectively per every 10 ppb increase in concentration, and the effect of O3 is 1.11% (0.98%, 1.24%), 1.39% (1.19%, 1.59%), and 1.82% (1.39%, 2.26%), and OX is 1.77% (1.58%, 1.97%), 2.19% (1.90%, 2.48%), and 2.90% (2.29%, 3.52%). Notably, women and individuals aged over 75 years exhibit higher susceptibility to these pollutants, with NO2 showing a greater impact, especially during the warm seasons. The elevated mortality rates associated with NO2, O3, and OX underscore the significance of addressing air pollution as a pressing public health issue, especially in controlling NO2 and O3 together. Further research is needed to explore the underlying mechanisms and possible influential factors of these effects.

Associations between home environmental factors and childhood eczema and related symptoms in different cities in China.

Previous studies have shown significant associations between home environmental factors and childhood eczema. However, few studies have compared how associations differ in different regions. This study investigated associations between home environmental factors and childhood eczema ever, and related symptoms including itchy rash (IR) and being awakened by itchy rash at night (awake by IR) in 4 cities located in different regions of China, based on cross-sectional investigations during 2010-2012. We used two-step analysis to explore the associations between influencing factors and eczema/related symptoms: first, group Least Absolute Shrinkage and Selection Operator (LASSO) was conducted to identify important factors among a list of candidates; then, the associations in total study population and in each city were estimated using logistic regression. We found these home environmental factors to be risk factors for eczema or related symptoms: large residence size, shared room, air cleaner at home, abnormal smell, perceived dry air, visible mold or damp stains, cooking with coal or wood, painted wall, incense, mice, new furniture during pregnancy, abnormal smell at birth, window condensation at birth and environmental tobacco smoke at birth. Environmental protective factors were rural house location and window ventilation. Associations of factors with eczema/related symptoms differed across cities. For example, air conditioning was protective for eczema in Beijing and awakening by IR in Shanghai with ORs of 0.70 (95%CI: 0.52, 0.95) and 0.33 (95%CI: 0.14, 0.81) respectively, but not significant in other cities. Our results have implications for improving home environments to reduce the risk of childhood eczema/related symptoms in different regions of China.

Association of Short-Term Co-Exposure to Particulate Matter and Ozone with Mortality Risk.

A complex regional air pollution problem dominated by particulate matter (PM) and ozone (O3) needs drastic attention since the levels of O3 and PM are not decreasing in many parts of the world. Limited evidence is currently available regarding the association between co-exposure to PM and O3 and mortality. A multicounty time-series study was used to investigate the associations of short-term exposure to PM1, PM2.5, PM10, and O3 with daily mortality from different causes, which was based on data obtained from the Mortality Surveillance System managed by the Jiangsu Province Center for Disease Control and Prevention of China and analyzed via overdispersed generalized additive models with random-effects meta-analysis. We investigated the interactions of PM and O3 on daily mortality and calculated the mortality fractions attributable to PM and O3. Our results showed that PM1 is more strongly associated with daily mortality than PM2.5, PM10, and O3, and percent increases in daily all-cause nonaccidental, cardiovascular, and respiratory mortality were 1.37% (95% confidence interval (CI), 1.22-1.52%), 1.44% (95% CI, 1.25-1.63%), and 1.63% (95% CI, 1.25-2.01%), respectively, for a 10 µg/m3 increase in the 2 day average PM1 concentration. We found multiplicative and additive interactions of short-term co-exposure to PM and O3 on daily mortality. The risk of mortality was greatest among those with higher levels of exposure to both PM (especially PM1) and O3. Moreover, excess total and cardiovascular mortality due to PM1 exposure is highest in populations with higher O3 exposure levels. Our results highlight the importance of the collaborative governance of PM and O3, providing a scientific foundation for pertinent standards and regulatory interventions.

Characterization of chemical transport in human skin and building material.

Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) are ubiquitous in indoor environment. They can emit from source into air, and subsequently penetrate human skin into blood through dermal uptake, causing adverse health effects. This study develops a two-layer analytical model to characterize the VOC/SVOC dermal uptake process, which is then extended to predict VOC emissions from two-layer building materials or furniture. Based on the model, the key transport parameters of chemicals in every skin or material layer are determined via a hybrid optimization method using data from experiments and literature. The measured key parameters of SVOCs for dermal uptake are more accurate than those from previous studies using empirical correlations. Moreover, the association between the absorption amount of studied chemicals into blood and age is preliminarily investigated. Further exposure analysis reveals that the contribution of dermal uptake to the total exposure can be comparable with that of inhalation for the examined SVOCs. This study makes the first attempt to accurately determine the key parameters of chemicals in skin, which is demonstrated to be critical for health risk assessment.

Chemical element concentrations in cord whole blood and the risk of preterm birth for pregnant women in Guangdong, China.

Maternal exposure to chemical elements, including essential and non-essential elements, have been found to be associated with preterm births (PTB). However, few studies have measured element concentrations in cord whole blood, which reflects activity at the maternal-fetal interface and may be biologically associated with PTBs. In this study, we determined concentrations of 21 elements in cord whole blood and explored the associations between element concentrations and PTB in a nested case-control study within a birth cohort in Guangdong, China. Finally, 515 preterm infants and 595 full-term infants were included. We performed single-element and multi-element logistic regressions to evaluate linear relationships between element concentrations and PTB. According to the results of single-element models, most essential elements (including K, Ca, Si, Zn, Se, Sr and Fe) were negatively associated with PTB, while Cu, V, Co and Sn were positively associated with PTB. Of the non-essential elements, Sb, Tl, and U were positively associated with PTB, while Pb was negatively associated with PTB. The multi-element model results for most elements were similar, except that the association between Mg and PTB was shown to be significantly positive, and the association for Cu became much larger. A possible explanation is that the effects of Mg and Cu may be influenced by other elements. We performed restricted cubic spline (RCS) regressions and found significantly non-linear exposure-response relationships for Mg, Se, Sr, K and Sb, indicating that the effects of these elements on PTB are not simply detrimental or beneficial. We also examined the joint effect using a Bayesian kernel machine regression (BKMR) model and found the risk of PTB decreased significantly with element mixture concentration when lnC was larger than the median. Bivariate interaction analysis suggested antagonistic effects of Sb on Zn and Sr, which may be attributed to Sb negating the antioxidant capacity of Zn and Sr. This study provides additional evidence for the effect of element exposures on PTB, and will have implications for the prevention of excessive exposures or inappropriate element supplementation during pregnancy.

The association between daily-diagnosed COVID-19 morbidity and short-term exposure to PM1 is larger than associations with PM2.5 and PM10.

Exposure to particulate matter (PM) could increase both susceptibility to SARS-CoV-2 infection and severity of COVID-19 disease. Prior studies investigating associations between PM and COVID-19 morbidity have only considered PM2.5 or PM10, rather than PM1. We investigated the associations between daily-diagnosed COVID-19 morbidity and average exposures to ambient PM1 starting at 0 through 21 days before the day of diagnosis in 12 cities in China using a two-step analysis: a time-series quasi-Poisson analysis to analyze the associations in each city; and then a meta-analysis to estimate the overall association. Diagnosed morbidities and PM1 data were obtained from National Health Commission in China and China Meteorological Administration, respectively. We found association between short-term exposures to ambient PM1 with COVID-19 morbidity was significantly positive, and larger than the associations with PM2.5 and PM10. Percent increases in daily-diagnosed COVID-19 morbidity per IQR/10 PM1 for different moving averages ranged from 1.50% (-1.20%, 4.30%) to 241% (95%CI: 80.7%, 545%), with largest values for exposure windows starting at 17 days before diagnosis. Our results indicate that smaller particles are more highly associated with COVID-19 morbidity, and most of the effects from PM2.5 and PM10 on COVID-19 may be primarily due to the PM1. This study will be helpful for implementing measures and policies to control the spread of COVID-19.

A rapid and robust method to determine the key parameters of formaldehyde emissions from building and vehicle cabin materials: Principle, multi-source application and exposure assessment.

The ubiquity of formaldehyde emitted in indoor and in-cabin environments can adversely affect health. This study proposes a novel full-range C-history method to rapidly, accurately and simultaneously determine the three key parameters (initial emittable concentration, partition coefficient, diffusion coefficient) that characterize the emission behaviors of formaldehyde from indoor building and vehicle cabin materials, by means of hybrid optimization. The key parameters of formaldehyde emissions from six building materials and five vehicle cabin materials at various temperatures, were determined. Independent experiments and sensitivity analysis verify the effectiveness and robustness of the method. We also demonstrate that the determined key parameters can be used for predicting multi-source emissions from different material combinations that are widely encountered in realistic indoor and in-cabin environments. Furthermore, based on a constructed vehicle cabin and the determined key parameters, we make a first attempt to estimate the human carcinogenic potential (HCP) of formaldehyde for taxi drivers and passengers at two temperatures (25 °C, 34 °C). The HCP for taxi drivers at both temperatures exceeds 10-6 cases, indicating relatively high potential risk. This study should be helpful for pre-evaluation of indoor and in-cabin air quality, and can assist designers in selecting appropriate materials to achieve effective source control.

Residential building materials: An important source of ambient formaldehyde in mainland China.

This study investigates the contribution of formaldehyde from residential building materials to ambient air in mainland China. Based on 265 indoor field tests in 9 provinces, we estimate that indoor residential sources are responsible for 6.66% of the total anthropogenic formaldehyde in China's ambient air (range for 31 provinces: 1.88-18.79%). Residential building materials rank 6th among 81 anthropogenic sources (range: 2nd-10th for 31 provinces). Emission intensities show large spatial variability between and within regions due to different residential densities, emission characteristics of building materials, and indoor thermal conditions. Our findings indicate that formaldehyde from the indoor environment is a significant source of ambient formaldehyde, especially in urban areas. This study will help to more accurately evaluate exposure to ambient formaldehyde and its related pollutants, and will assist in formulating policies to protect air quality and public health.

A Validation Study of a Locally Adapted Brussels Infant and Toddler Stool Scale of the Chinese Version.

The Brussels Infant and Toddler Stool Scale was developed to improve the reliability of constipation diagnosis in non-toilet-trained children. The aim of this study was to evaluate the validity of simplified Chinese versions of the Brussels Infant and Toddler Stool Scale when used by parents, community doctors, pediatricians, and nurses. Photographs of the Scale were categorized into four categories (hard stools, formed stools, loose stools, and watery stools) and subjects assigned each photograph to a category. The study included two stages. In the first stage (n = 237 observers), percent correct allocations of the seven photographs ranged from 68.4% to 93.2%. We observed poorer recognition of the three hard stool items (77.4%, 85.8%, and 74.0%) than had been reported in the original Brussels Infant and Toddler Stool Scale validity study (95.9%, 93.4%, and 96.2%). Because hard stool items were commonly miscategorized as formed stools (21.6%, 9.5%, and 26.0%), we modified the descriptors "hard stools" and "formed stools" into "dry/hard stools" and "formed loose stools," respectively, and examined the performance of the modified Chinese Brussels Infant and Toddler Stool Scale in stage 2 of our study. The proportions of correct allocations of the three "hard stool" items in the modified Chinese Brussels Infant and Toddler Stool Scale increased to 94.7%, 90.4%, and 84.6%, values that were statistically similar to those reported previously in the original Brussels Infant and Toddler Stool Scale publisher. Renaming these categories to remove ambiguity in Chinese improved the identifiability of these items. The resultant Chinese Brussels Infant and Toddler Stool Scale was found to be valid for use with Chinese observers.

Estimation of ambient PM2.5 in Iraq and Kuwait from 2001 to 2018 using machine learning and remote sensing.

Iraq and Kuwait are in a region of the world known to be impacted by high levels of fine particulate matter (PM2.5) attributable to sources that include desert dust and ambient pollution, but historically have had limited pollution monitoring networks. The inability to assess PM2.5 concentrations have limited the assessment of the health impact of these exposures, both in the native populations and previously deployed military personnel. As part of a Department of Veterans Affairs Cooperative Studies Program health study of land-based U.S. military personnel who were previously deployed to these countries, we developed a novel approach to estimate spatially and temporarily resolved daily PM2.5 exposures 2001-2018. Since visibility is proportional to ground-level particulate matter concentrations, we were able to take advantage of extensive airport visibility data that became available as a result of regional military operations over this time period. First, we combined a random forest machine learning and a generalized additive mixed model to estimate daily high resolution (1 km × 1 km) visibility over the region using satellite-based aerosol optical depth (AOD) and airport visibility data. The spatially and temporarily resolved visibility data were then used to estimate PM2.5 concentrations from 2001 to 2018 by converting visibility to PM2.5 using empirical relationships derived from available regional PM2.5 monitoring stations. We adjusted for spatially resolved meteorological parameters, land use variables, including the Normalized Difference Vegetation Index, and satellite-derived estimates of surface dust as a measure of sandstorm activity. Cross validation indicated good model predictive ability (R2 = 0.71), and there were considerable spatial and temporal differences in PM2.5 across the region. Annual average PM2.5 predictions for Iraq and Kuwait were 37 and 41 µg/m3, respectively, which are greater than current U.S. and WHO standards. PM2.5 concentrations in many U.S. bases and large cities (e.g. Bagdad, Balad, Kuwait city, Karbala, Najaf, and Diwaniya) had annual average PM2.5 concentrations above 45 µg/m3 with weekly averages as high as 150 µg/m3 depending on calendar year. The highest annual PM2.5 concentration for both Kuwait and Iraq were observed in 2008, followed by 2009, which was associated with extreme drought in these years. The lowest PM2.5 values were observed in 2014. On average, July had the highest concentrations, and November had the lowest values, consistent with seasonal patterns of air pollution in this region. This is the first study that estimates long-term PM2.5 exposures in Iraq and Kuwait at a high resolution based on measurements data that will allow the study of health effects and contribute to the development of regional environmental policies. The novel approach demonstrated may be used in other parts of the world with limited monitoring networks.

Impacts of El Niño-Southern Oscillation on surface dust levels across the world during 1982-2019.

Dust pollution has become a significant concern worldwide. Both human activities and climate conditions affect dust levels. This study investigates the influence of El Niño-Southern Oscillation (ENSO), an important large-scale climate phenomenon, on surface dust levels in different regions. We used surface dust concentrations from Retrospective analysis for Research and Applications version 2 reanalysis and Southern Oscillation index (SOI) as dust and ENSO indicators, respectively. First, we first described characteristics of the global surface dust concentrations spanning a period of 37 years (1982-2019). Subsequently, we investigated the associations between monthly surface dust concentrations and SOI in regions with relative high dust levels, (i.e., North Africa, Northwest China and Mongolia, the Middle East, and South Australia) using time-series generalized additive models, controlled for meteorological variables and normalized difference vegetation index (NDVI). In order to capture the delayed effects of ENSO on dust, we fitted the model for SOI with 13 different moving averages starting from 12 months before. The highest average surface dust concentration for our study regions was 306.68 µg/m3, observed in North Africa. The average dust concentrations in the Middle East, Northwest China, and South Australia were 193.18, 113.64, and 77.19 µg/m3, respectively. Our results showed that dust concentrations were positively related with SOI. The associations between dust and SOI were more significant and higher for North Africa and the Middle East. Our results indicated that for regions with high dust pollution, La Niña episodes are associated with increased dust concentrations, while El Niño events are associated with decreased dust concentrations.

Trace element concentrations in ambient air as a function of distance from road.

Traffic-related air pollution is associated with various adverse health effects. In the absence of more complicated exposure assessment techniques, many environmental health studies have used the natural logarithm of distance to road as a proxy for traffic-related exposures. However, research validating this proxy and further explaining the spatial patterns and elemental composition of traffic-related particulate matter air pollution remains limited. In this study, we collected air samples using a mobile particle concentrator that allowed for high sample loading from major roadways in the Greater Boston Area. We found that concentrations of Cl, Ti, V, Cr, Mn, Fe, Co, Cu, Zn, Sr, Zr, Sn, Ba, and Pb were significantly associated with the natural logarithm of distance to road in coarse particulate matter, and total fine particulate mass concentrations of Al, Ca, Ti, Cr, Mn, Fe, Cu, and Zn were significantly associated with natural logarithm of distance to road in fine particulate matter. Road type (A1 or A2 [primary roads or highways] versus A3 [secondary and connecting roads]) was not a significant predictor of any traffic-related elements in particulate matter air pollution. Our results help identify traffic-related elements in particulate matter air pollution and support the use of logarithm of distance to road as a proxy for traffic-related particulate matter air pollution exposure assessment in epidemiological studies.

Trace element mass fractions in road dust as a function of distance from road.

Road dust particles play an important role in atmospheric pollution and are associated with adverse human health effects. Traffic emissions are a major source of particles in road dust. However, there has been limited information about the relationship between distance from road and traffic-related elements levels in road dust. We investigated the relationships between proximity to the nearest major roadway and trace element mass fractions in PM10 and PM2.5 re-suspended from the road surface, based on measurements at three different distance ranges. We found that mass fractions of Ba, Cu, Zr, Zn, Cl, Co, Cr, Ca, Ti in PM10 road dust as well as Zr, Cu, Cl, Zn, Cr, Ti, Mn, Ca, Ni, and Fe in PM2.5 road dust, significantly decreased with distance from major road. Most of these elements are associated with road traffic emissions, including both tailpipe and non-tailpipe emissions. The decrease rates differed among elements due to differences in local traffic contributions. The decreases for elements which are mainly associated with non-tailpipe traffic emissions (e.g., Ba, Zr) were more dramatic. Our results indicate that traffic emissions, especially non-tailpipe emissions, contribute substantially to road dust, suggesting the need for control strategies for non-tailpipe emissions. Implications: We investigated the relationships between road proximity with trace element mass fractions in PM10 and PM2.5 re-suspended from the road surface. We observed significant decrease of traffic-related elements in PM10 and PM2.5 road dust with log distance from major road. We also found that the mass fractions for elements, which mainly come from traffic decrease more sharply compared to elements which come from both traffic and other sources. Our results indicate that traffic emissions contribute substantially to road dust, and imply that the distance to major road can be used as a proxy for ambient exposure.

Effects of particulate matter gamma radiation on oxidative stress biomarkers in COPD patients.

Inhalation of particulate matter (PM) radioactivity is an important pathway of ionizing radiation exposure. We investigated the associations between short-term exposures to PM gamma radioactivity with oxidative stress in COPD patients. Urinary concentrations of 8-hydroxy-2'-deoxyguanosine (8-OHdG) and malondialdehyde (MDA) of 81 COPD patients from Eastern Massachusetts were measured 1-4 times during 2012-2014. Daily ambient and indoor PM gamma activities (gamma-3 through gamma-9) were calculated based on EPA RadNet data and indoor-outdoor infiltration ratios. Linear mixed-effects models were used to examine the associations between biomarkers with PM gamma activities for moving averages from urine collection day to 7 days before. Our results indicate that ambient and indoor PM gamma activities were positively associated with 8-OHdG, with stronger effects for exposure windows closer to urine collection day. For per interquartile range increase in indoor PM gamma activities averaged over urine collection day and 1 day before, 8-OHdG increased from 3.41% (95% CI: -0.88, 7.88) to 8.87% (95% CI: 2.98, 15.1), adjusted for indoor black carbon. For MDA, the timing of greatest effects across the exposure week varied but was nearly all positive. These findings provide insight into the toxigenic properties associated with PM radioactivity and suggest that these exposures promote systemic oxidative stress.

Characterization of phthalates in sink and source materials: Measurement methods and the impact on exposure assessment.

The fate and transport of semi-volatile organic compounds (SVOCs) in residential environments is significantly influenced by emission and sorption processes, which can be characterized by three key parameters: the gas-phase SVOC concentration adjacent to the material surface (y0); the diffusion coefficient (Dm); and the partition coefficient (K). Accurate determination of these three key parameters is critical for investigating SVOC mass transfer principles, and for assessing human health risks. Based on the mass transfer process of phthalates in a ventilated chamber, a novel method is developed to simultaneously measure Dm and K (key sorption parameters) in sink materials. The Dm and K of four target phthalates in a common T-shirt (sink material) are determined, and compared with those reported in literature. Results demonstrate that the measured parameters are in good agreement with those previously reported (relative deviation < 20 %), validating the effectiveness of proposed method. In addition, this method can be applied to determine y0, a key parameter from source materials. Results indicate that y0 determined with this method is consistent with that measured by literature method. Finally, dermal exposure analysis is performed, showing that dermal uptake of target phthalates is greatly affected by clothes.

Association between ambient beta particle radioactivity and lower hemoglobin concentrations in a cohort of elderly men.

Although ionizing radiation is known to have detrimental effects on red blood cells, the effect of environmental radioactivity associated with ambient particulate matter (PM) is unknown. We hypothesized that exposure to ambient PM-associated beta particle radioactivity (PRß) would be associated with a lower hemoglobin concentration. We studied 1.704 participants from the Normative Aging Study (NAS) over 36 years (1981-2017) who lived in Eastern, MA and the surrounding area. Exposures to PRß was assessed using USEPA's RadNet monitoring network that measures gross beta radiation associated with ambient PM. Mixed effect models with a random intercept adjusting for potential confounders was used, including ambient black carbon (BC) and particulate matter ≤2.5 µm (PM2.5) concentrations. Greater cumulative PRß activities at 7-, 14-, 21- and 28-days before the hemoglobin determination were associated with lower hemoglobin concentrations. The greatest effect was for a 28-day moving average. An IQR of 0.83 × 10-4 Bq/m3 of ambient PRß was associated with a 0.12 g/dL decrease in hemoglobin concentration (95%CI: -0.18 to -0.05). The effects of PRß were similar when the models were adjusted for ambient BC or PM2.5. This is the first study to demonstrate an association between environmental ionizing radiation released from particulate matter with a lower hemoglobin concentration, suggesting that ambient radiation may contribute to the development of anemia.

Short-term exposure to ambient particle gamma radioactivity is associated with increased risk for all-cause non-accidental and cardiovascular mortality.

BACKGROUND: Recent studies have found that particulate matter (PM) attached radioactivity was associated with certain adverse health effects including increased blood pressure and lung dysfunction. However, there has been no investigation on the direct effect of PM radioactivity on mortality. METHODS: Exposures to ambient PM gamma activities were determined using U.S. EPA RadNet data. Data on daily deaths were obtained from individual state Departments of Public Health. We used a generalized additive quasi-Poisson model to estimate the associations between two-day average ambient PM gamma activities (gamma2 through gamma9) with all-cause non-accidental and cardiovascular daily deaths for each of 18 US cities, for each season, adjusting for two-day average PM2.5 exposure, temperature, relative humidity, day of week and long-term trends. Subsequently, we used random-effects meta-analysis to estimate the overall effect in the 18 cities for each season. RESULTS: We found that all-cause non-accidental daily mortality in spring season was positively associated with two-day average ambient PM gamma activities in spring, with significant results for gamma2, gamma5 and gamma6. Similarly, cardiovascular daily mortality was positively associated with two-day average ambient PM gamma activities, with significant results for gamma2, gamma4, gamma5, gamma6, gamma7 and gamma9. For the spring season, each interquartile range (IQR) increase of two-day averaged ambient PM gamma activity was associated with increase in all-cause daily deaths, ranging from 0.15% (95% Confidence Interval (CI): -0.36%, 0.65%) to 1.03 (95%CI: 0.18%, 1.89%). Each IQR was also associated with increase in cardiovascular daily deaths, ranging from 0.01% (95%CI: -0.89, 0.92) to 2.95% (95%CI: 1.33, 4.59). For other seasons overall we found statistically insignificant associations of PM radioactivity with mortality. CONCLUSIONS: Our findings suggest that there are potential systemic toxic effects of inhalation of radionuclides attached to ambient air particles.